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Environmental Catching-Up, Eco-Innovation, and Technological Leadership in China's Pilot Ecological Civilization Zones

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Environmental Catching-Up, Eco-Innovation, and Technological Leadership in China's Pilot Ecological Civilization Zones TFS-18528; No of Pages 9 Technological Forecasting & Social Change xxx (2016) xxx–xxx Contents lists available at ScienceDirect Technological Forecasting & Social Change Environmental catching-up, eco-innovation, and technological leadership in China's pilot ecological civilization zones Yanni Yu a,WenjieWub, Tao Zhang c,⁎,YanchuLiud a Institute of Resource, Environment and Sustainable Development, College of Economics, Jinan University, Guangzhou, Guangdong 510632, China b School of Energy, Geoscience, Infrastructure and Society, Heriot-Watt University, Edinburgh EH14 4AS, UK c Department of Marketing, Birmingham Business School, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK d Lingnan College, Sun Yat-Sen University, Guangzhou 510275, China article info abstract Article history: In this study we propose a global metafrontier Luenberger productivity indicator (GMLPI) to investigate the effect Received 24 December 2015 of the establishment of the Poyang Lake Eco-economic Zone (PLEEZ), one of China's typical ecological civilization Received in revised form 5 May 2016 zones, on regional environmental total-factor productivity growth. We combine the global environmental tech- Accepted 14 May 2016 nology, metafrontier approach, and the non-radial Luenberger productivity indicator and incorporate the region- Available online xxxx al heterogeneities into the environmental productivity growth analysis. This GMLPI includes the efficiency change, technological change, and metafrontier technology gap change indices. An empirical study of the Keywords: Environmental total-factor productivity PLEEZ has been conducted using the county level data covering a period from 2009 to 2013. Empirical results Metafrontier non-radial Luenberger show that the environmental productivity growth has increased by 8.71% on average, with growth primarily productivity indicator driven by technological change. These results suggest that the establishment of the PLEEZ is effective in encour- Poyang lake Eco-economic Zone aging eco-innovation; however the PLEEZ lacks an eco-leadership effect. Significant heterogeneities in environ- mental productivity growth and its patterns among three major functional zones in the PLEEZ remain. © 2016 Elsevier Inc. All rights reserved. 1. Introduction widely used for measuring productivity change growth. Taking the environmental factors into account, Chung et al. (1997) proposed The Poyang Lake Eco-economic Zone Planning was officially ap- the Malmquist–Luenberger index for measuring environmentally proved by the State Council of China on December 12th, 2009, indicating sensitive productivity growth. Empirical studies applying the that the construction of the Poyang Lake Eco-economic Zone (PLEEZ) Malmquist–Luenberger index include Weber and Domazlicky was a national-level strategy. The PLEEZ is based on the Poyang lake (2001), Färe et al. (2001), Yörük and Zaim (2005), Kumar (2006) urban circle and is intended to become an ecological economic demon- and Zhang and Choi (2013a,b), for measuring environmental perfor- stration zone and a low-carbon economy development priority zone in mance change. China.1 The increasing interest in and strategic importance of the PLEEZ The Luenberger productivity indicator is an alternative for measur- have heightened the need for investigating its effects on regional envi- ing productivity growth. Compared with the Luenberger indicator, the ronmental performance. Malmquist index appears to overestimate productivity changes Therefore this study investigates the effect of the PLEEZ's establish- (Boussemart et al., 2003). Recent work also suggests that the ment on regional environmental productivity growth after 2009. A sig- Luenberger index is more robust than the Malmquist index (Fujii nificant growth of the environmental productivity of the PLEEZ after et al., 2014). Thus, this study employs the Luenberger indicator as its 2009 indicates that the PLEEZ policy is effective. main methodology. However, the basic Luenberger indicator cannot Two kinds of indices are widely used for measuring productivity deal with the non-zero slack variable problem because it adopts the ra- growth, i.e. the Malmquist index and the Luenberger indicator. The dial method for measuring performance (Zhou et al., 2012; Zhang et al., Malmquist index, empirically presented by Färe et al. (1994),is 2014). To handle this shortcoming, Fujii et al. (2014) proposed the non- radial Luenberger indicator with undesirable outputs. To incorporate cross-group heterogeneity into this indicator, Zhang and Wei (2015) in- troduced a metafrontier non-radial Luenberger carbon emission perfor- ⁎ Corresponding author. E-mail addresses: [email protected] (Y. Yu), [email protected] (T. Zhang). mance index; unlike Zhang and Wei (2015), who focused on single- 1 For details about the PLEEZ, please see Appendix A. factor carbon emission performance change, we propose a metafrontier http://dx.doi.org/10.1016/j.techfore.2016.05.010 0040-1625/© 2016 Elsevier Inc. All rights reserved. Please cite this article as: Yu, Y., et al., Environmental catching-up, eco-innovation, and technological leadership in China's pilot ecological civilization zones, Technol. Forecast. Soc. Change (2016), http://dx.doi.org/10.1016/j.techfore.2016.05.010 2 Y. Yu et al. / Technological Forecasting & Social Change xxx (2016) xxx–xxx non-radial Luenberger productivity indicator to measure the total- to scale may then be expressed as follows: factor environmentally sensitive productivity growth. Compared with the methodologies adopted in existing energy and environmental stud- XN ; ; : ≤ ; ; :::; ; ies (e.g. Wang et al., 2013, 2015; Zhang and Wei, 2015),2 the key inno- T ¼fðÞx y b znxmn xm m ¼ 1 M n¼1 vativeness of the proposed approach is that it can handle both non-zero XN slack variables and cross-group heterogeneity simultaneously. We then z y ≥y ; s ¼ 1; :::; S; n sn s ð2Þ use the proposed approach to measure environmental productivity n¼1 XN growth and its patterns in the PLEEZ at a county level. z b ¼ b ; j ¼ 1; :::; J; This study has two major contributions to the current literature. n jn j n¼1 Practically, although a number of studies have focused on the environ- zn ≥0; n ¼ 1; ⋯; Ng: mental productivity growth for China's provinces (Zhang et al., 2011; Choi et al., 2015) or China's industries (Chen and Golley, 2014; Li and where M, S and J denote the number of inputs, desirable outputs and un- Lin, 2015), no studies have explored the PLEEZ, a national-level strategy. desirable outputs, respectively. This study thus addresses this research gap by evaluating the PLEEZ, After defining the environmental technology, the non-radial direc- thus enabling us to get insight into the effectiveness of this national- tional distance function (DDF) is followed. The formal definition of the level strategy. Methodologically, we develop an integrated methodolo- non-radial DDF was first introduced by Zhou et al. (2012). Compared gy called the Global Metafrontier non-radial Luenberger Productivity In- with other energy and environmental modeling techniques, a unique dicator (GMLPI) to measure environmental productivity growth. This advantage of DDF is its capability of expanding desirable outputs and methodology combines a non-radial directional distance function, lessening inputs or undesirable outputs simultaneously. A review of Luenberger productivity indicator, and the global metafrontier ap- DDF application in energy and environmental studies can be found in proach. It can thus incorporate slack variables, undesirable outputs, Zhang and Choi (2014). Following Zhou et al. (2012), the non-radial and group heterogeneities when measuring environmental productivi- DDF with undesirable output is defined as: ty growth. The remainder of this paper is organized as follows. Section 2 intro- ! ÈÉ D ðÞ¼x; y; b; g sup wT β : ðÞðÞþx; y; b g Á diagðÞβ ∈T : ð3Þ duces the methodology used. Section 3 conducts the empirical study. Section 4 concludes this study. x y b T where w =(wm,ws,wj ) denotes a normalized weight vector corre- sponding to the number of inputs and outputs, g =(−gx,gy,−gb)isan β βx βy βb T ≥ 2. Methodology explicit directional vector, and =( m, s, j ) 0denotesthescaling ! factors indicating the inefficiencies. Thus the value of D ðx; y; b; gÞ 2.1. Non-radial directional distance function under the environmental technology can be calculated by solving the following DEA-type model: We assume that there are j =1,…, N observations, which are differ- ∈ℜM ! x y b ent counties in the PLEEZ, and each region uses input vector x + to D ðÞx; y; b; g ¼ max wx β þ wyβ þ wbβ ∈ℜS m m s s j j produce good economic output vector y + as well as undesirable XN pollutant vector b ∈ℜJ . Thus, the environmental production technolo- : : ≤ −βx ; ; :::; ; + s t znxmn xm mgxm m ¼ 1 M gy can be expressed as follows: n¼1 XN ≥ βy ; ;::: ; znysn ys þ s gys s ¼ 1 S ð4Þ ; ; : ; ; n¼1 T ¼ fgðÞx y b x can produce ðÞy b ð1Þ XN −βb ; ; ::: ; znbjn ¼ b j j gbj j ¼ 1 J n¼1 ≥ ; ; ; ⋯; where T is the environmental production technology. We assume that it zn 0 n ¼ 1 2 N βx ; βy; βb ≥ : satisfies the standard axioms of production theory (Färe and Grosskopf, m s j 0 2005). That is, finite amounts of inputs can produce only finite outputs. Inputs and desirable outputs are often assumed to be freely (strong) dis- The directional vector g can be set up in different ways, based on posable. For modeling joint-production technologies (Färe et al., 1989) ! given policy goals. If D ðx; y; b; gÞ¼0, then the specificunittobeevalu- with undesirable outputs, weak disposability and null-jointness as- ated is located on the frontier of the best practices in the direction of g. sumptions should be imposed on the environmental production tech- nology T, as follows: 2.2. Global metafrontier Luenberger productivity indicator (GMLPI) (i) If (x,y,b) ∈ T and 0 ≤ θ ≤ 1, then (x,θy,θb) ∈ T; Following Zhang and Choi (2013a,b) and Zhang and Wei (2015), (ii) If (x,y,b) ∈ T and b =0,theny =0. three environmental technologies: contemporaneous, intertemporal, and global environmental technologies are needed to define the GMLPI and its decompositions.
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